sampling

问题 For my experiment I have 20 categories which contain 9 pictures each. I want to show these pictures in a pseudo-random sequence where the only constraint to randomness is that one image may not be followed directly by one of the same category. So I need something similar to r = randi([1 20],1,180); just with an added constraint of two numbers not directly following each other. E.g. 14 8 15 15 7 16 6 4 1 8 is not legitimate, whereas 14 8 15 7 15 16 6 4 1 8 would be. An alternative way I was

问题 For my experiment I have 20 categories which contain 9 pictures each. I want to show these pictures in a pseudo-random sequence where the only constraint to randomness is that one image may not be followed directly by one of the same category. So I need something similar to r = randi([1 20],1,180); just with an added constraint of two numbers not directly following each other. E.g. 14 8 15 15 7 16 6 4 1 8 is not legitimate, whereas 14 8 15 7 15 16 6 4 1 8 would be. An alternative way I was

问题 I'm trying to run my Nucleo f401re on 80mhz from HSE int F4xxx::clockInit(int pllM, int pllN, int pllP, int pllQ) { enableHse(); //FLASH CLEAR_BIT(FLASH->ACR, FLASH_ACR_PRFTEN); FLASH->ACR&= ~FLASH_ACR_LATENCY; FLASH->ACR |= FLASH_ACR_LATENCY_5WS | FLASH_ACR_ICEN | FLASH_ACR_DCEN|FLASH_ACR_PRFTEN; //set HSE as PLL source RCC->PLLCFGR = RCC_PLLCFGR_PLLSRC_HSE; // RCC->CR &= ~(RCC_CR_PLLON); //disable PLL before changes // RCC->PLLCFGR = pllM|(pllN<<6)|(((pllP>>1)-1)<<16)|RCC_PLLCFGR_PLLSRC_HSE

问题 I'm trying to run my Nucleo f401re on 80mhz from HSE int F4xxx::clockInit(int pllM, int pllN, int pllP, int pllQ) { enableHse(); //FLASH CLEAR_BIT(FLASH->ACR, FLASH_ACR_PRFTEN); FLASH->ACR&= ~FLASH_ACR_LATENCY; FLASH->ACR |= FLASH_ACR_LATENCY_5WS | FLASH_ACR_ICEN | FLASH_ACR_DCEN|FLASH_ACR_PRFTEN; //set HSE as PLL source RCC->PLLCFGR = RCC_PLLCFGR_PLLSRC_HSE; // RCC->CR &= ~(RCC_CR_PLLON); //disable PLL before changes // RCC->PLLCFGR = pllM|(pllN<<6)|(((pllP>>1)-1)<<16)|RCC_PLLCFGR_PLLSRC_HSE

问题 Suppose I have 8-bits (mono and stereo) .wav files. When processing of this file I have to declare pointer to array of samples. Suppose I create array for samples. Then if it is mono , I read each sample using for(i = 0; i < n; i++ ) . Q: How can I access right and left channels separately (stereo)? PS I've read a lot about "mono, stereo and *.wave" but still I can't understand how can I realise access to each channell separately... 回答1: You still have array of samples, the question is how

问题 I have a data frame as such Customer Day 0. A 1 1. A 1 2. A 1 3. A 2 4. B 3 5. B 4 and I want to sample from it but I want to sample different sizes for each customer. I have the size of each customer in another dataframe. For example, Customer Day 0. A 2 1. B 1 Suppose I want to sample per customer per day. So far I have this function: def sampling(frame,a): return np.random.choice(frame.Id,size=a) grouped = frame.groupby(['Customer','Day']) sampled = grouped.apply(sampling, a=??).reset

问题 I am confused on the order of feature selection, sampling and cross validation, My dataset has 468 rows and 23000 columns, out of which 269 belong to class I and 199 belong to class II , The data when split to train and test has [215 class I and 159 class II in train ][54 class I and 40 class II in test].Due to less number of samples I had to apply SMOTE oversampling on the train data to reduce bias. Or should I apply Under Sampling here which leads to data loss resulting in much smaller

问题 I'm simulating a one-dimensional and symmetric random walk procedure: y[t] = y[t-1] + epsilon[t] where white noise is denoted by epsilon[t] ~ N(0,1) in time period t . There is no drift in this procedure. Also, RW is symmetric, because Pr(y[i] = +1) = Pr(y[i] = -1) = 0.5 . Here's my code in R: set.seed(1) t=1000 epsilon=sample(c(-1,1), t, replace = 1) y<-c() y[1]<-0 for (i in 2:t) { y[i]<-y[i-1]+epsilon[i] } par(mfrow=c(1,2)) plot(1:t, y, type="l", main="Random walk") outcomes <- sapply(1

问题 Background I'm working on a music player, and want any sort of audio visualizer to be part of it. I've already made a previous post specifically targeting python-vlc, but I guess not too many people know about it. Here is the post in question: How to get audio samples from python-VLC What I need I need a way to listen to audio output, preferably by application although it is not completely necessary. It must be a python module. What I found A bunch of tutorials regarding audio input from the

问题 I have implemented an alternate parameterization of the negative binomial distribution in R, like so (also see here): nb = function(n, l, a){ first = choose((n + a - 1), a-1) second = (l/(l+a))^n third = (a/(l+a))^a return(first*second*third) } Where n is the count, lambda is the mean, and a is the overdispersion term. I would like to draw random samples from this distribution in order to validate my implementation of a negative binomial mixture model, but am not sure how to go about doing